discipline-refactor-phase-2-planning
Sub-skill of discipline-refactor: Phase 2: Planning.
Best use case
discipline-refactor-phase-2-planning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of discipline-refactor: Phase 2: Planning.
Teams using discipline-refactor-phase-2-planning should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/phase-2-planning/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How discipline-refactor-phase-2-planning Compares
| Feature / Agent | discipline-refactor-phase-2-planning | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of discipline-refactor: Phase 2: Planning.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Phase 2: Planning
## Phase 2: Planning
**Spawn**: `Task` with `subagent_type=Plan`
**Call**: `@skill-creator` for new discipline skills
**Prompt**:
```
Create module-based migration plan based on Phase 1 analysis.
Context: {analysis_results}
Create plan for ALL directories:
1. Package identification:
- Confirm package name: <package_name>
- Confirm disciplines: [_core, discipline-1, discipline-2, ...]
2. Code structure (src/):
BEFORE: src/<package>/feature1/, src/<package>/feature2/
AFTER: src/<package>/modules/_core/, src/<package>/modules/<discipline>/
3. Test structure:
BEFORE: tests/test_feature1.py, tests/integration/
AFTER: tests/modules/_core/, tests/modules/<discipline>/
4. Documentation structure:
BEFORE: docs/api/, docs/guides/
AFTER: docs/modules/_core/, docs/modules/<discipline>/
5. Specs structure:
BEFORE: specs/feature-spec.md, specs/plan.md
AFTER: specs/modules/<discipline>/, specs/templates/
6. Data structure (if exists):
BEFORE: data/raw/, data/processed/
AFTER: data/modules/<discipline>/
7. Skills structure:
BEFORE: .Codex/skills/category/
AFTER: .Codex/skills/<discipline>/
8. Import updates:
- from <package>.feature → from <package>.modules.<discipline>
- Update __init__.py files
- Update relative imports
9. Create README.md for each module with:
- Module purpose
- Key files
- Dependencies on other modules
Output executable task list for Phase 3.
```
---Related Skills
external-drive-ingest-planning
Plan safe external-drive ingests into repo-aligned storage such as /mnt/ace: read-only mounts, manifests, staged rsync, dedupe-merge gates, GitHub issue traceability, and governance/execution split.
planning-lane-cross-review-permission-fallback
Handle overnight planning-only lanes where plan revision/editing works but real cross-provider review dispatch is permission-blocked.
overnight-planning-noop-run-salvage
Recover when unattended overnight Codex planning runs exit 0 but produce no required artifacts; salvage the wave by auditing existing plan state, generating missing summary artifacts manually, and preserving morning monitoring surfaces.
large-parallel-planning-wave-environment-failure-handoff
Handle large pre-plan-review planning waves that succeed analytically but fail to persist artifacts due to quota exhaustion, sandbox write failures, or cancelled GitHub mutations.
gtm-prospect-pipeline-phased-execution
Phased execution pattern for
github-visual-planning-issues
Create review-friendly GitHub planning issues that supersede stale/seasonal issues and include source-backed image thumbnails for faster human review.
planning-goal
Goal-Oriented Action Planning (GOAP) specialist that dynamically creates intelligent plans to achieve complex objectives. Use for multi-step tasks with dependencies, adaptive replanning, complex deployment workflows, or when a high-level goal needs systematic breakdown into achievable actions.
planning-code-goal
Code-centric Goal-Oriented Action Planning integrated with SPARC methodology. Use for feature implementation planning, performance optimization goals, testing strategy development, or any software development objective requiring systematic breakdown with measurable success criteria.
issue-planning-mode
Mandatory planning workflow for ALL GitHub issues — plan, review, approve, then implement.
gh-work-planning
Canonical GitHub issue planning route — issue intake, strengthened resource intelligence, repo-tracked plan artifact, adversarial review, GitHub progress posting, future-issue capture, explicit approval gate before execution, and execution-ready delegation packaging for Codex agent teams.
gh-work-planning-checklist
Compact live-execution checklist companion for the canonical gh-work-planning route. Use for fast operational tracking during issue planning without replacing the full route.
continuous-planning-pipeline
Maintain a standing day/night GitHub issue pipeline so agents always have planned, reviewed, user-approved work for overnight execution and next-day QA/approval.